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dc.contributor.authorWang, Ping
dc.contributor.authorZheng, Jin
dc.contributor.authorFu, Linyun
dc.contributor.authorPatton, Evan
dc.contributor.authorLebo, Tim
dc.contributor.authorDing, Li
dc.contributor.authorLiu, Qing
dc.contributor.authorLuciano, Joanne
dc.contributor.authorMcGuinness, Deborah
dc.date.accessioned2022-02-18T02:38:02Z
dc.date.available2022-02-18T02:38:02Z
dc.date.issued2011-10-23
dc.identifier.other182
dc.identifier.urihttp://archive.tw.rpi.edu/media/latest/wang2011iswc-swqp-v2.1.pdf
dc.identifier.urihttps://hdl.handle.net/20.500.13015/4584
dc.description.abstractWe present a semantic technology-based approach to emerging monitoring systems based on our linked data approach in the Tetherless World Constellation Semantic Ecology and Environment Portal (SemantEco). Our integration scheme uses an upper level monitoring ontology and mid-level monitoring-relevant domain ontologies. The initial domain ontologies focus on water and air quality. We then integrate domain data from different authoritative sources and multiple regulation ontologies (capturing federal as well as state guidelines) to enable pollution detection and monitoring. An OWL-based reasoning scheme identifies pollution events relative to user chosen regulations. Our approach captures and leverages provenance to enable transparency. In addition, SemantEco features provenance-based facet generation, query answering, and validation over the integrated data via SPARQL. We introduce the general SemantEco approach, describe the implementation which has been built out substantially in the water domain creating the SemantAqua portal, and highlight some of the potential impacts for the future of semantically-enabled monitoring systems.
dc.relation.urihttps://tw.rpi.edu/project/SemantAQUA
dc.subjectSemantic Water Quality Portal
dc.titleA Semantic Portal for Next Generation Monitoring Systems


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